World-Renowned Author and Advisor Cautions That Project Management Will Become Irrelevant Without Rapid Transformation
AI shifts PM toward leadership: AI cuts admin work and lets project leaders focus on purpose, alignment, and impact.
AI augments leaders, not replaces them: The best leaders use AI for insight and speed, while keeping empathy and judgment human.
PM must evolve fast: Organizations need modern, AI-enabled project practices or risk becoming irrelevant.
Antonio Nieto-Rodriguez has helped some of the world's biggest companies realize their strategies through projects. He also literally wrote the book on project management and launched the AI Project Management Certification with APMG International.
He's concerned that project management isn't changing fast enough to stay relevant in this time of transformation, so we sat down with him to get his view of what's happening — and what needs to happen.
Projects have become the new operating model for modern organizations
I'm an author, advisor, and passionate advocate for the idea that projects are the most powerful vehicles for change ever invented by humankind.
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Over the past 25 years, I’ve worked across continents helping organizations — from multinationals like PwC, BNP Paribas, and GlaxoSmithKline to global institutions like the World Bank and the United Nations — turn strategy into reality through projects. I’ve served as chair of the Project Management Institute and currently lead Projects & Company, a firm dedicated to helping organizations and leaders transition into the Transformation Age.
My earlier Harvard Business Review book, The Harvard Business Review Project Management Handbook, began with a simple yet provocative idea: “Everyone is a project manager, but most don’t know it.”
My upcoming book, Powered by Projects (HBR Press, January 2026), takes this one step further: “Every organization is project-driven — but most leaders don’t know it.”
In it, I argue that our world is moving beyond traditional hierarchies into an era where projects are the new operating model. The companies that will thrive are those that can continuously transform themselves through well-led, purposeful projects.
And, together with Ricardo Vargas, I designed the AI in Project Management Masterclass and launched the AI Project Management (AIPM) Certification with APMG International. In just over a year, more than 600 professionals from over 60 countries have completed the program. They represent a new generation of leaders — people who understand that the value of AI isn’t in replacing project managers, but in augmenting them.
Why AI is the most transformative force in the history of project management
I see AI as the most transformative force in the history of project management.
For decades, project professionals have invested huge amounts of time and energy in tracking, reporting, and administration — activities that, while necessary, often kept us from focusing on what truly drives success: clarity of purpose, alignment, and leadership.
Today, AI in project management is stripping away much of that friction. It automates scheduling, risk tracking, stakeholder summaries, and progress reporting — freeing up leaders to concentrate on higher-order thinking: strategic clarity, engagement, and impact.
In my own daily work, I now spend far less time on operational oversight and far more on strategic integration — helping organizations redesign how they deliver transformation in an AI-enabled world.
The question I used to ask was, “How can I finish this project faster?”
Now, I ask, “How can I make this project matter more?”
That shift is profound: from efficiency to relevance, from deliverables to outcomes, from management to leadership.
AI isn’t replacing project managers — it’s revealing what great project leaders have always done best: Connecting purpose with progress.
AI isn’t replacing project managers — it’s revealing what great project leaders have always done best: Connecting purpose with progress.
What AI can and can’t do in real-world project delivery
AI is ideally suited for knowledge-heavy, repetitive, and data-driven tasks:
- Automating reporting, risk logs, and document generation
- Drafting communication templates and meeting summaries
- Identifying early warning signs in project data
The good news is that these tasks are the ones that most project managers don't like to do. The heart of project management — trust, judgment, and storytelling — remains human.
You can’t automate empathy. You can’t train a model to read the mood of a team after a failed milestone. AI can process emotion, but it cannot feel it.
The great project leaders of tomorrow will master both: They’ll let AI handle the “science of delivery” so they can focus on the “art of leadership.”
In my work, I’ve witnessed, firsthand, the rise of what I call the AI-Augmented Project Leader. These are the traits that I see in each one:
- Someone who uses AI to gather insights, not just data
- Someone who delegates repetition to algorithms, but keeps judgment and storytelling human
- Someone who guides meaning instead of just managing tasks
Our world is moving beyond traditional hierarchies into an era where projects are the new operating model. The companies that will thrive are those that can continuously transform themselves through well-led, purposeful projects.
How AI improves visibility, alignment, and decision-making in projects
AI doesn’t solve complexity — it illuminates it.
In project management, we often assume that more technology means more control. In reality, AI exposes the underlying mess faster. It highlights duplication, inefficiency, and, most uncomfortably, misalignment between purpose and execution.
At first, this is disorienting. But once you embrace it, AI becomes a mirror for continuous improvement. It tells you not what to fix next quarter, but what to fix now.
When I introduced AI-assisted decision dashboards — built via Lovable — to an executive committee recently, one leader said: “I feel like we’ve been flying an airplane in clouds, and someone just removed the fog.”
That’s precisely it — AI doesn’t give you new wings; it gives you vision.
The “fog” was the typical noise and uncertainty around priorities, resources, and ownership. The dashboard revealed overlaps in projects and gaps in resourcing that had been buried in spreadsheets. By surfacing these, AI gave the team immediate clarity.
A real-world example of how AI improves large-scale project delivery
A recent example comes from a large global consumer goods company managing over 200 active transformation initiatives. Historically, their executives struggled to understand where value was truly being created. They had plenty of dashboards, but very little insight.
We deployed an AI-powered “Project Intelligence Platform” that aggregated data from across their systems — Excel, Jira, Power BI, and even HR pulse surveys — and then layered AI analytics on top to spot patterns humans usually miss. This was a custom deployment that combined multiple AI components from different LLMs to analyze sentiment, risks, and project signals holistically.
Within days, we uncovered patterns that no human analyst had spotted: For instance, projects with low stakeholder sentiment scores were twice as likely to fail in later phases.
This prompted a radical rethink of their governance model. Reviews shifted from pure budget and schedule control to engagement and purpose reviews. And leaders began asking, “Do people still believe in this project?” — a question that proved more predictive of success than any KPI.
Six months later, delivery efficiency improved by 30%, costs dropped by €12 million, and morale surged. But beyond metrics, what really changed was the organization’s consciousness about how projects reflect its culture and values.
Why removing repetitive work with AI gives the most leverage
I’m not actively building multi-agent orchestration or autonomous delivery bots. That’s not where my focus is right now. What I am doing is much simpler and, in my view, more valuable in the short term: I’m learning how to use basic coding and automation to remove repetitive work from my day.
For example, I’ve started using ChatGPT to write small scripts to clean survey data, generate first-draft project reports, and organize stakeholder feedback into structured formats — risks, dependencies, sponsors, and follow-up actions. Before, I would do this manually in PowerPoint and Excel. Now, the workflow is: Gather raw inputs → run a script or lightweight automation → get a structured draft I can review, challenge, and refine.
That matters for two reasons:
- Scale of attention: Every project leader today is overloaded. The real bottleneck is not data — it’s cognitive bandwidth. Automating the “assembly work” gives me space to think strategically, instead of spending my evenings formatting slides and status packs.
- Speed of insight: I can now test ideas faster. Instead of waiting days for someone to analyze stakeholder signals and spot emerging risks, I can generate a view myself in minutes and take it into a leadership conversation the same day.
So for now, my path is not “replace the project manager with an AI agent.” It’s “augment the project manager with small, very targeted automations.” I’m much more interested in giving project leaders leverage than in pretending the project can run itself.
For now, my path is not “replace the project manager with an AI agent.” It’s “augment the project manager with small, very targeted automations.” I’m much more interested in giving project leaders leverage than in pretending the project can run itself.
How AI is reshaping core project delivery rituals and workflows
Over the past few years, I’ve seen that the biggest challenge for organizations isn’t choosing between Agile and Waterfall — it’s learning to blend them intelligently. We’re entering an era of hybrid project leadership, where the right mix of methods, data, and human intuition defines success.
AI is accelerating this transition. It gives us the ability to integrate the discipline of traditional project management with the adaptability of Agile — turning methodology into a living system that learns.
In practice, this means rethinking our core rituals:
- Defining scope is no longer a one-off exercise: With AI tools like MS Project Copilot and Miro Assist, we can run rapid scenario simulations that test multiple project scopes or delivery paths before we commit. Instead of rigid plans, we create adaptive roadmaps that evolve as new data becomes available.
- Aligning teams now blends human dialogue and digital insight: I use AI to analyze meeting transcripts or stakeholder feedback to detect misalignment early — something humans often sense too late. But alignment still happens in human conversation; AI only provides the mirror. To do this, I typically combine Otter.ai (note taking software for meeting summaries and misalignment detection), Miro Assist (online collaboratiion tool), and Power BI AI Insights (project forecasting software for interdependency analysis). The power comes from using them together rather than relying on one tool.
- Managing execution has become a hybrid ritual, too: AI dashboards — built via Lovable — help track interdependencies and forecast risks with remarkable precision, while teams use Agile rituals — stand-ups and retrospectives — to maintain ownership and speed. One of my favorite examples is how some teams use AI copilots to generate summaries of retrospectives, highlighting recurring patterns that humans can then discuss and interpret.
Still, as I've said, the essence of project leadership hasn’t changed — it’s about judgment, empathy, and meaning. AI can inform decisions, but it can’t inspire commitment.
A minimalist AI tech stack for modern project leaders
The list of AI tools that can be used is endless. MS Project Copilot, Notion AI, Grain, Otter.ai, Miro Assist, and Asana Intelligence can support scenario simulation, transcript analysis, and early risk detection. For dashboards, platforms like Power BI AI Insights and Tableau Pulse work well.
But for me, the evolution of my stack has been away from complexity. Here's my intentionally-minimalist stack:
- ChatGPT for coding and automation
- NotebookLM for engaging ways of communication
- Miro for collaborative design and stakeholder mapping
- Lovable for executive dashboards
- And Custom GPTs trained on my project canvas methodology
Five years ago, every team wanted more project management tools. Now we want fewer — but smarter — ones. The most powerful stack is not the one with the most features, but the fewest distractions.
How a custom project-delivery GPT can expand a team’s cognitive capacity
Speaking of Custom GPTs, my most significant breakthrough over the past year has been our internal Project GPT Assistant — a conversational AI trained on more than 20 years of my real project experience, case studies, templates, and playbooks.
It acts as a true copilot for project delivery. It drafts project charters, synthesizes stakeholder interviews, builds risk matrices, and even generates narratives or metaphors for executive storytelling. In essence, it’s like having a junior consultant who never sleeps — but who has read every document I’ve ever produced.
A good example: Earlier this year, I was supporting a multinational bank on a large digital transformation program involving 80+ initiatives. Traditionally, summarizing insights from dozens of stakeholder interviews and aligning them into a single strategic message would have taken my team three to four days of manual work.
With the Project GPT Assistant, we uploaded the interview transcripts, and within 20 minutes, it had generated:
- A concise synthesis of recurring themes
- A draft of the executive summary for the kickoff presentation
- A set of “early warning signals” extracted from language patterns around resistance and risk
We spent the next 48 hours thinking strategically — interpreting the results, defining priorities, and crafting a compelling change narrative.
That’s the real benefit. In the past, AI was seen as a way to speed up the mechanical side of project management. What I’ve discovered is that it also expands our cognitive capacity. It allows us not only to work faster but also to think more deeply.
A call for urgency in the project management community
The project management profession is not changing fast enough to stay relevant in the age of AI. Not yet.
For too long, project management has been trapped in its own success. We’ve built frameworks, certifications, and methodologies that worked beautifully for a world of predictability and control — but that world is gone.
Most organizations still manage projects with mindsets and tools from the 1970s. Meetings, reports, templates… It’s as if the rest of the business world is racing ahead, and project management is jogging behind, clipboard in hand.
AI is the wake-up call we can’t ignore. It’s not just automating the administrative parts of our job — it’s rewriting the rules of how work gets done, how teams form, and how value is delivered.
If we don’t evolve fast, project management risks becoming irrelevant — a discipline that explains the past instead of shaping the future. That’s why I’m calling for a sense of urgency in our community.
This is the time to reinvent, to question everything, to break old habits and design new ones that match the speed, fluidity, and intelligence of the world we now live in.
Five years ago, every team wanted more tools. Now we want fewer — but smarter — ones. The most powerful stack is not the one with the most features, but the fewest distractions.
How the next decade will redefine project management and leadership
Because, from what I'm seeing, the next decade will redefine what it means to manage and to lead.
- Every organization will become project-driven — transformation will no longer be optional.
- Every leader will need to master project thinking — strategy will live and die through projects.
- Every project team will be AI-augmented — humans will focus on creativity, empathy, and ethics, while AI handles data, forecasting, and pattern detection.
In many ways, we’re witnessing the birth of a new profession: The Project Leader of the Transformation Age. Future CEOs will act like Chief Project Officers — allocating resources dynamically based on real-time project intelligence.
The organizations that embrace this shift will thrive. Those that don’t will slowly become irrelevant.
Practical advice for leading your organization's transformation
My advice for this transformation comes down to three simple principles:
- Fall in love with the problem, not the process: Don’t rush into execution. Take time to understand the real “why.”
- Use AI to see further, not faster: More speed without clarity just amplifies confusion.
- Build trust before technology: No algorithm can fix a broken culture.
If you don’t create space for your teams to reflect, learn, and connect purpose with action, no technology will save you.
And finally, ask yourself: “Are you leading transformation — or just surviving it?”
Follow along
To explore more of Antonio Nieto-Rodriguez's work and thinking, head to the following links:
And here's his upcoming book: Powered by Projects: The Future of Organizations in the Transformation Age (Harvard Business Review Press, January 2026)
More expert interviews to come on The Digital Project Manager!